On the other hand, for open chemical networks, which contain inflow and outflow as in (REF ), there are not many model reduction methods available that are specific for such open CRN. In [1]}, it has been shown that a time-scale separation can be used to reduce the model via singular perturbation theory; akin to the QSSA approach for closed CRN above. In [2]}, it introduced an automated model reduction pipeline based on QSSA where it gives robustness guarantees for structured model reduction of linear and nonlinear dynamical systems under parametric uncertainties. When the open CRN does not have a clear time-scale separation, this approach can no longer be applicable. In [3]}, it is shown that the Kron reduction approach can be applicable to open CRN. Another work for open CRN is the use of balanced truncation applied to the associated variational systems obtained through linearization of the systems [4]}. For open nonlinear CRN, it remains a challenge to solve the corresponding balanced truncation PDE for such networks [5]}.
